In this paper, we describe ontology-based text categorization in which the domain ontologies are automatically acquired through morphological rules and statistical methods. The on...
Traditional text classification algorithms are based on a basic assumption: the training and test data should hold the same distribution. However, this identical distribution assum...
For manyknowledgeintensive applications, it is necessary to have extensive domain-specific knowledgein addition to general-purpose knowledge bases usually built around MachineRead...
When research articles introduce new findings or concepts they typically relate them only to knowledge and domain concepts of immediate relevance. However, many domain concepts re...
Increasingly large text datasets and the high dimensionality associated with natural language create a great challenge in text mining. In this research, a systematic study is cond...
M. Mahdi Shafiei, Singer Wang, Roger Zhang, Evange...